Cited by 110Visual perception and processing mechanismsMemory Processes and InfluencesDecision-Making and Behavioral Economics

The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.

The impact of evidence reliability on sensitivity and bias in decision confidence.

Open access
Boldt, Annika, de Gardelle, Vincent, Yeung, Nick·2017·Journal of Experimental Psychology: Human Perception and Performance

Abstract

Human observers effortlessly and accurately judge their probability of being correct in their decisions, suggesting that metacognitive evaluation is an integral part of decision making. It remains a challenge for most models of confidence, however, to explain how metacognitive judgments are formed and which internal signals influence them. While the decision-making literature has suggested that confidence is based on privileged access to the evidence that gives rise to the decision itself, other lines of research on confidence have commonly taken the view of a multicue model of confidence. The present study aims at manipulating one such cue: the perceived reliability of evidence supporting an initial decision. Participants made a categorical judgment of the average color of an array of eight colored shapes, for which we critically manipulated both the distance of the mean color from the category boundary (evidence strength) and the variability of colors across the eight shapes (evidence reliability). Our results indicate that evidence reliability has a stronger impact on confidence than evidence strength. Specifically, we found that evidence reliability affects metacognitive readout, the mapping from subjectively experienced certainty to expressed confidence, allowing participants to adequately adjust their confidence ratings to match changes in objective task performance across conditions. (PsycINFO Database Record

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1037/xhp0000404

Cites

72 of 72 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 (A) Sample stimuli, showing the four difficulty conditions in the 2 (mean) × 2 (variance) design. Color values are made more extreme for illustrative purposes. (B) Design of the color task; participants had to indicate whether an array of eight colored shapes was on average more red or more blue by pressing the left or right response key. After making their response, the confidence scale was presented on screen and participants were given unlimited time to choose how confident they were that their last response was correct. RSI: response-stimulus interval; max. = maximum.
Figure 1 (A) Sample stimuli, showing the four difficulty conditions in the 2 (mean) × 2 (variance) design. Color values are made more extreme for illustrative purposes. (B) Design of the color task; participants had to indicate whether an array of eight colored shapes was on average more red or more blue by pressing the left or right response key. After making their response, the confidence scale was presented on screen and participants were given unlimited time to choose how confident they were that their last response was correct. RSI: response-stimulus interval; max. = maximum.CC BY · PubMed Central
Figure 2 (A) Distributions of confidence levels displayed for correct and error trials separately. (B) Confidence for the four difficulty color conditions (together for both error and correct trials). All error bars are within-subject confidence intervals (Loftus & Masson, 1994).
Figure 2 (A) Distributions of confidence levels displayed for correct and error trials separately. (B) Confidence for the four difficulty color conditions (together for both error and correct trials). All error bars are within-subject confidence intervals (Loftus & Masson, 1994).CC BY · PubMed Central
Figure 3 (A) Standardized regression coefficients for three different models to predict confidence. Colored xs reflect the respective parameters that were not considered in the regression model. (B) Signed t values for three different models to predict confidence. The horizontal dashed lines highlight the critical t values, so that model parameters above or below the dashed, horizontal lines are significantly different from zero. (C) Mean R2 and (D) mean BICs for these models. RT = reaction time; BIC = Bayesian information criterion.
Figure 3 (A) Standardized regression coefficients for three different models to predict confidence. Colored xs reflect the respective parameters that were not considered in the regression model. (B) Signed t values for three different models to predict confidence. The horizontal dashed lines highlight the critical t values, so that model parameters above or below the dashed, horizontal lines are significantly different from zero. (C) Mean R2 and (D) mean BICs for these models. RT = reaction time; BIC = Bayesian information criterion.CC BY · PubMed Central
Figure 4 Nonparametric Type II SDT parameter estimates as a function of difficulty. (A) AROC expresses metacognitive sensitivity. (B) BROC expresses metacognitive bias. All error bars are within-subject confidence intervals (Loftus & Masson, 1994). SDT = signal detection theory; ROC = receiver operating characteristic.
Figure 4 Nonparametric Type II SDT parameter estimates as a function of difficulty. (A) AROC expresses metacognitive sensitivity. (B) BROC expresses metacognitive bias. All error bars are within-subject confidence intervals (Loftus & Masson, 1994). SDT = signal detection theory; ROC = receiver operating characteristic.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 71 references

Cited by

Sorted by citations

Items 101–109 of 109

Metadata

Authors
Boldt, A., de Gardelle, V., & Yeung, N.
Affiliations
  • University of Oxford (GB)
  • Centre d'Économie de la Sorbonne (FR)
Corresponding author
Boldt, Annika
Venue
Journal of Experimental Psychology: Human Perception and Performance
Published
2017-08
Volume
43
Issue
8
Pages
1520-1531
ISSN
  • 0096-1523 (ISSN-L)
  • 1939-1277
OpenAlex
W2605154204
Cited by
110
References
71
Citations by year
2026: 15 · 2025: 10 · 2024: 13 · 2023: 11 · 2022: 13 · 2021: 13 · 2020: 9 · 2019: 13 · 2018: 9 · 2017: 4
FWCI
5.49
Type
journal article
Language
en
Open access
Locations
  • Journal of Experimental Psychology Human Perception & Performance (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • UCL Discovery (University College London) (submittedVersion)
Funders
Economic and Social Research Council
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords
metacognition, decision confidence, reliability of evidence, quality of evidence, confidence bias, categorical judgment, variability, confidence calibration
MeSH terms
Metacognition, Adolescent, Adult, Color Perception, Decision Making, Female, Humans, Judgment, Male, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review